Learning Outcomes

identify or describe the characteristics of intelligent agents and the environments that they can inhabit;

​identify, contrast and apply to simple examples the major search techniques that have been developed for problem-solving in AI;

​distinguish the
characteristics, and advantages and disadvantages, of the major
knowledge representation paradigms that have been used in AI, such as
production rules, semantic networks, propositional logic and first-order
logic;

Learning Strategy

Formal Lectures

Practicals

Private Study

Formal lectures: Students will be expected to attend three hours of formal lectures in a typical week. Formal lectures will be used to introduce students to the concepts and methods covered by the module, reinforced by practical illustrations and exercises.

Practicals: Students will be expected to attend five hours of supervised computer lab practicals to coincide with the teaching of the Prolog material. Computer lab practicals are intended to allow students to undertake practical exercises and get involved in hands-on learning of the Prolog programming language.

Private study: In a typical week students will be expected to devote six hours of unsupervised time to private study; private study will provide time for reflection and consideration of lecture material, background reading and study for the assessment tasks.

Assessment: Continuous assessment will be used to test to what extent knowledge of the lecture material has been learnt and also to test practical skills. A final examination at the end of the module will assess the academic achievement of students.